For a variety of sensing applications, it is important to determine the shape of sensed objects that emit electromagnetic radiation. For example, in passive ranging applications such as in obtaining a map based on infrared signatures of a terrain having hills and valleys, it is necessary to determine the elevation of the hills and the depths of the valleys. There are numerous ways of solving this problem, but the known methods for determining the height, width, and depth of hills and valleys using infrared imagery require the use of multiple sensors or multiple views with a single sensor at different points. Techniques that determine shape from image shading are available for visible imagery. There is a need, however, for a similar technique using infrared imagery, because of the importance of infrared imagery in defense applications.
For example, with known methods if an infrared image is to be used to determine the shape of a three-dimensional object, it is necessary either to have two sensors for two separate infrared images of the particular object at the same time, or to take a first image at one point and a second image at another point with the same infrared sensor. With these two images, computer correlation of the images is possible. The computer correlation permits an analysis and determination of the shape of the particular object.
The principal limitation associated with this correlation approach is that it requires extensive computer processing. Additionally, this stereo sensor approach either requires the precise operation of two separate sensors or, alternatively, requires a longer flying period or viewing time to obtain the different positions necessary for multiple image orientations. The two sensor solution poses a more complicated correlation problem than the single sensor solution. However, in a hostile environment, such as when an aircraft must assess a potential target, the increased viewing time for the second infrared image with the same sensor often increases the risk of attack for the viewing aircraft.
While there are methods that use a single sensor to estimate the shape of a target that reflects electromagnetic radiation, these methods determine the shape of a three-dimensional object that reflects electromagnetic radiation reflected radiation may include light waves, millimeter waves, or microwaves that go to the three dimensional object and bounce from its surface. An example of a method of this type may be seen in, B. K. P. Horn, Robot Vision, The MIT Press, Cambridge, Mass., (1986), which presents a technique for estimating the shape of a three-dimensional object from shading using television imagery. For the situation where the object only emits instead of reflecting electromagnetic radiation such as in infrared emission, the laws of physics are different. Consequently, it is not possible to use the same approach to determine the surface shape of the object.
Thus there is a need for a method and system that permits shape estimation from electromagnetic radiation emitted from three-dimensional objects.
There is a need for an improved method of shape estimation for military and other uses that overcomes the problem of having to use stereo cameras or stereo camera images and thereby the need for more extensive computing capability and the need for greater periods of time to record the image of the emitted radiation.
Moreover, there is the need for a method and system that can establish the shape of an object that emits infrared radiation, and does not rely on the laws of physics appropriate only for the reflection electromagnetic radiation.